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distilbert-base-uncased__subj__train-8-2
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3081
- Accuracy: 0.8755
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7146 | 1.0 | 3 | 0.6798 | 0.75 |
0.6737 | 2.0 | 6 | 0.6847 | 0.75 |
0.6519 | 3.0 | 9 | 0.6783 | 0.75 |
0.6105 | 4.0 | 12 | 0.6812 | 0.25 |
0.5463 | 5.0 | 15 | 0.6869 | 0.25 |
0.4922 | 6.0 | 18 | 0.6837 | 0.5 |
0.4543 | 7.0 | 21 | 0.6716 | 0.5 |
0.3856 | 8.0 | 24 | 0.6613 | 0.75 |
0.3475 | 9.0 | 27 | 0.6282 | 0.75 |
0.2717 | 10.0 | 30 | 0.6045 | 0.75 |
0.2347 | 11.0 | 33 | 0.5620 | 0.75 |
0.1979 | 12.0 | 36 | 0.5234 | 1.0 |
0.1535 | 13.0 | 39 | 0.4771 | 1.0 |
0.1332 | 14.0 | 42 | 0.4277 | 1.0 |
0.1041 | 15.0 | 45 | 0.3785 | 1.0 |
0.082 | 16.0 | 48 | 0.3318 | 1.0 |
0.0672 | 17.0 | 51 | 0.2885 | 1.0 |
0.0538 | 18.0 | 54 | 0.2568 | 1.0 |
0.0412 | 19.0 | 57 | 0.2356 | 1.0 |
0.0361 | 20.0 | 60 | 0.2217 | 1.0 |
0.0303 | 21.0 | 63 | 0.2125 | 1.0 |
0.0268 | 22.0 | 66 | 0.2060 | 1.0 |
0.0229 | 23.0 | 69 | 0.2015 | 1.0 |
0.0215 | 24.0 | 72 | 0.1989 | 1.0 |
0.0211 | 25.0 | 75 | 0.1969 | 1.0 |
0.0172 | 26.0 | 78 | 0.1953 | 1.0 |
0.0165 | 27.0 | 81 | 0.1935 | 1.0 |
0.0132 | 28.0 | 84 | 0.1923 | 1.0 |
0.0146 | 29.0 | 87 | 0.1914 | 1.0 |
0.0125 | 30.0 | 90 | 0.1904 | 1.0 |
0.0119 | 31.0 | 93 | 0.1897 | 1.0 |
0.0122 | 32.0 | 96 | 0.1886 | 1.0 |
0.0118 | 33.0 | 99 | 0.1875 | 1.0 |
0.0097 | 34.0 | 102 | 0.1866 | 1.0 |
0.0111 | 35.0 | 105 | 0.1861 | 1.0 |
0.0111 | 36.0 | 108 | 0.1855 | 1.0 |
0.0102 | 37.0 | 111 | 0.1851 | 1.0 |
0.0109 | 38.0 | 114 | 0.1851 | 1.0 |
0.0085 | 39.0 | 117 | 0.1854 | 1.0 |
0.0089 | 40.0 | 120 | 0.1855 | 1.0 |
0.0092 | 41.0 | 123 | 0.1863 | 1.0 |
0.0105 | 42.0 | 126 | 0.1868 | 1.0 |
0.0089 | 43.0 | 129 | 0.1874 | 1.0 |
0.0091 | 44.0 | 132 | 0.1877 | 1.0 |
0.0096 | 45.0 | 135 | 0.1881 | 1.0 |
0.0081 | 46.0 | 138 | 0.1881 | 1.0 |
0.0086 | 47.0 | 141 | 0.1883 | 1.0 |
0.009 | 48.0 | 144 | 0.1884 | 1.0 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3